Daily Archives: April 12, 2018

Are You Ready to Get Analytical But Don’t Know How? Read On!

Now that you’ve read our last three posts and understand that you need to get more analytical if you want to get cognitive, hopefully you’re ready to dive deeper but just don’t know how to do that.

The four part answer is almost as easy as it was for optimization, just a bit more nuanced. What’s the nuance? Figuring out if your provider offers a modern spend analytics platform or is still a generation (or two) behind (when you are still behind yourself) is the nuance. So how do you determine if a vendor at least passes the sniff test? We’ll get to that, but first, let’s talk about where you start.

At a high-level, the four-part answer is almost the same as optimization. Just the vendor names change.

1) If you are using a sourcing or analytics platform from a modern provider with modern (next generation) analytics capability, use it (and acquire the module if necessary).

Who are the vendors? While we can’t say this list is thoroughly exhaustive, if you look at Spend Matters Deep Solution map, you see that the following providers make the map: AnyData, (SAP) Ariba, (Opera) BIQ, GEP, iValua, Jaggaer, Sievo, Simfoni, SpendHQ, Synertrade, and Zycus. Not all are equal, and this list is likely not exhaustive, but depending on your organizational needs, a sub-set of these providers is likely your starting point. (What Sub-Set? Depending on whether you are data, function, process, technology, configurability, or services oriented, the sub-set will vary. And practitioners who want to know which vendors match which subset can contact Spend Matters.) And if you are a do-it-yourself type, you could probably start with a platform like Spendata.

2) If you are not using a modern analytics platform or a modern sourcing platform with analytics, get a modern analytics platform or a modern sourcing platform with analytics, your choice.

Again, you can start with the dozen of providers above, which you can quickly narrow down depending on whether you prefer best of breed or sourcing suite and whether you favour technical orientations or service orientations. If the list is still too large, find the subset that bests fits your organizational size, industry, category focus, geography, and culture and focus in on those.

3) If you are using another sourcing or analytics (reporting) platform that is not meeting your needs, and can replace it, do so.

As with the optimization providers, a few of these providers have a considerable portion of their customer base that consist of customers that switched from another provider with a solution that didn’t meet their needs and, thus, have a lot of experience with change management, fear squashing, migrating your data over, and getting you up and running on the right processes quickly. Simply craft the right RFI and you will quickly zero in to the handful of providers that will likely be the best fit for your situation.

4) If you are using another sourcing platform or reporting platform that is otherwise meeting your needs, or can’t be replaced at the present time, or both, augment it with a pure-play deep-dive best of breed modern analytics solution.

So if you are in the situation that you just bought a best of breed Source-to-Contract or Source-to-Pay solution and can’t replace it, or you have a first generation BI tool that produces reports the executives love but doesn’t meet your needs, augment it with a point-based best of breed solution. From the above list,
AnyData, (Opera) BIQ, Sievo, Simfoni, SpendHQ, and Spendata fit that bill.

But what about the “sniff test”?

How do you differentiate a last generation solution from a current generation solution? Three tests. Have them, in front of you, in a live demo:

  • Build a Cube with Derived Dimensions and a new Report on the Cube on the Spot
    if they can’t do so (in 15 minutes), they are a last generation platform that can only work on pre-defined and pre-built OLAP cubes
  • Run a categorization exercise on at least 3 months of your transaction history / invoice data and at least 100,000 transactions
    if they can’t either use their AI, or powerful (collaborative) filtering and priority based rule definition, and get to the 95% mark in an hour, it’s not for you … (and, trust me, you don’t need AI to get to the 95% mark if the rule definition capability is appropriately defined)
  • Map the cube to a new taxonomy, create new derived dimensions, and create a set of filters that will allow comparison reports to be run between the cubes
    let’s face it, there is no one size fits all taxonomy for analysis, and this is the kicker test to see if the platform can support any taxonomy that is needed, run any analysis you want, and allow you to run comparison reports both as checksums and as differentials to figure out where the opportunities are hidden

All this should take less than a morning or afternoon. But it means the provider deserves to be on your short list.